Machine Learning Course Overview
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Develop Foundational Skills
In this Machine Learning course, gain a comprehensive understanding of how machine learning works to bring a technical perspective to the workplace.
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Apply Machine Learning
Learn to apply machine learning concepts to the real-world business problems your organization faces.
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Make Data-Driven Decisions
Use real data and select the relevant model to create a project, and learn how to leverage these frameworks and tools to make decisions.
Earn a BrainStation Machine Learning Certificate
When you complete your course, you will earn a BrainStation certificate, which can boost your LinkedIn profile and resume, helping you stand out in the job market.
Your Final Machine Learning Project
To earn your Machine Learning certificate, complete a machine learning project on a data set of your choosing. You'll structure your problem, develop a hypothesis, and select the artificial intelligence method that best suits your particular problem. Once you've implemented your model of choice, you'll optimize and present your findings.
What You'll Learn
Basic Methodology
Understand what machine learning is and learn about the various industry methods and terminology.
Problem Solving Methods
Gain confidence with supervised and unsupervised learning, regression, classification, clustering methods, and learn about neural networks, one of the most popular methods in the industry.
Machine Learning Process
Learn how to prepare your data, frame your problem, select the right machine learning model, and generate insights to support your decisions.
Best Practices
Adopt best practices for machine learning to ensure efficient and impactful work.
Learn From Industry Leading Guest Speakers
BrainStation students get access to exclusive guest lectures and panel discussion events led by some of the world's leading subject matter experts and professionals.
Recent Industry Guests
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Frank Bach
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Mike Giepert
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Alex Schleifer
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Samantha Yu
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Tehmina Haider
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Michael Katchen
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David Lennie
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Alexandria Stried
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Leanne Gibson
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Clare Carr
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Sukhmani Dev
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Satish Kanwar
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Laura Elsener
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Tom Keiser
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Michael Ayeoola
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Kirstine Stewart
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Sanyogita Shamsunder
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Sandy Carter
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Brittany Forsyth
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Nicole West
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Win Sakdinan
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Sharmeen Browarek Chapp
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Shimona Mehta
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Darren Murph
Interested in what a typical day looks like?
Step Into Your Virtual Classroom
BrainStation's online Machine Learning course provides an unmatched online learning experience, with a world-class learning platform, engaging live classes that emphasize collaboration and feedback, and comprehensive training and development resources.
Work together with fellow professionals in your class by splitting out into breakout rooms. This core part of our classroom experience allows you to get to know your classmates better and dive deeper on hands-on projects.
Online Live is powered by BrainStation's state-of-the-art learning management system. Seamlessly attend live lectures, access course content, work on projects, and more from any device.
What Our Students Are Saying
"My experience at BrainStation was nothing short of fantastic. The staff is extremely professional, insightful, and attentive. The facilities are superb and create an ideal environment for both learning and networking. I would definitely consider taking another BrainStation course to continue my professional development."
"The best part of my experience with BrainStation was the great Instructors and the well-organized course materials. I was very impressed with what we did in the class, which was heavily focused on hands-on projects."
"I've taken multiple professional development courses and BrainStation has by far been my favorite experience ... the teachers are professionals in the industry and always seem to be willing to take extra time outside of class to make sure you're staying up to speed."
"My experience at BrainStation was nothing short of fantastic. The staff is extremely professional, insightful, and attentive. The facilities are superb and create an ideal environment for both learning and networking. I would definitely consider taking another BrainStation course to continue my professional development."
"The best part of my experience with BrainStation was the great Instructors and the well-organized course materials. I was very impressed with what we did in the class, which was heavily focused on hands-on projects."
"I've taken multiple professional development courses and BrainStation has by far been my favorite experience ... the teachers are professionals in the industry and always seem to be willing to take extra time outside of class to make sure you're staying up to speed."
What our students say
The highlight was definitely the people. I think that's what makes the class so special.
Max Smillie, Regional Community Lead & Hub Curator at lululemon
Read Full Story
Join a Community of World-Class Professionals
When you take a BrainStation course, you are learning with the very best. Enroll today to tap into a global network of instructors and students at some of the most innovative organizations in the world.
Flexible Payment Options
BrainStation offers some of the most competitive payment options for digital learning, with a range of flexible payment plans.
To learn more about course fees and payment options, view our course package.
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Monthly Payment Plans
Split your tuition into smaller monthly payments.
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Employer Sponsorship
Get your tuition reimbursed by your employer.
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Scholarships
We offer a range of scholarships to make learning more accessible.
Please be advised: all scholarships must be approved and applied prior to enrollment in a BrainStation course or program.
Frequently Asked Questions
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Will I earn a Machine Learning Certificate?
Yes, when you complete this introduction to machine learning course, you will earn a Brainstation Machine Learning Certificate, which can boost your LinkedIn profile and resume, helping you stand out in the job market and when applying for data positions.
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Do I need to know math and statistics?
Yes, some knowledge of math and statistics will help learners to succeed in the Machine Learning course. To understand machine learning algorithms and neural networks, it’s a good idea to have a strong understanding of mathematics to keep up with the pace of the classroom.
Beyond the classroom, knowledge of algebra and calculus are important to enter the field of data science. It doesn’t hurt to have experience with computer science and software development as well, so that you can access databases and manipulate algorithms.
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What payment options do you offer?
BrainStation offers some of the most competitive payment options for machine learning training, with a range of flexible plans and scholarship opportunities.
These include:
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Monthly payment installments
Allowing you to split your tuition into smaller monthly payments.
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Employer sponsorship
Get your tuition reimbursed by your employer.
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Scholarships
We offer a range of scholarships to make learning machine learning more accessible.
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Monthly payment installments
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Are there any prerequisites for this Machine Learning course?
BrainStation’s Machine Learning course was created for those with some data experience, but who may be new to machine-learning and AI-specific algorithms and techniques. For this reason, a strong knowledge of Python is required.
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What tools and programming languages do we learn?
Throughout the Machine Learning course, you’ll gain a comprehensive understanding of how machine learning and artificial intelligence works, to bring a technical perspective to the workplace.
You’ll use tools like SQL and languages like Python and C++ to apply machine learning algorithms and leverage frameworks to make decisions.
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What’s the difference between the Data Science and Machine Learning courses?
BrainStation’s Machine Learning course covers material that is specific to machine learning (ML) and artificial intelligence (AI). By course’s end, you’ll have a comprehensive understanding of ML and AI that you can use in the workplace. This course requires knowledge of Python and data science to get started.
The Data Science course is an in-depth look at data science tools and techniques, including how to analyze large data sets, build predictive models, and create data visualizations in Python Packages. This is a broader understanding of the main responsibilities of a Data Scientist, as opposed to teaching the specific methodology behind machine learning algorithms, deep learning, and artificial intelligence.
